Inter-Temporal Variation in the Externalities of Peer-Firm Disclosures. Nemit Shroff MIT Sloan School of Management

Transcription

1 ACCOUNTING WORKSHOP Inter-Temporal Variation in the Externalities of Peer-Firm Disclosures By Nemit Shroff MIT Sloan School of Management Rodrigo S. Verdi* MIT Sloan School of Management Benjamin P. Yost MIT Sloan School of Management Thursday, May 26 th, :20 2:50 p.m. Room C06 *Speaker Paper Available in Room 447

2 Inter-Temporal Variation in the Externalities of Peer-Firm Disclosures Nemit Shroff MIT Sloan School of Management Rodrigo S. Verdi* MIT Sloan School of Management Benjamin P. Yost MIT Sloan School of Management First draft: September 2015 Current draft: March 2016 Abstract We study inter-temporal variation in the externalities a firm s disclosures has on its peers. Specifically, we predict and find that peer-firm disclosures have a larger economic effect on the cost of capital when firm-specific information is scarce, but that this effect shrinks as the amount of firm-specific information increases and substitutes for peer information. We conduct our analyses using a sample of private firms that raise public debt for the first time. We find that peerfirm disclosures lower bond yields by 15% for first-time capital raisers in the year of issuance but this effect declines to 2% by the third year post issuance. We corroborate our inference by examining the effect of peer disclosure on the cost of equity capital during initial and subsequent equity offerings. This paper provides novel evidence on inter-temporal changes in the economic consequences of disclosure externalities, which is an important justification for disclosure regulation. * Corresponding author contact information: 100 Main street, Cambridge, MA 02142; Phone: (617) ; rverdi@mit.edu. We appreciate helpful comments from Christine Botosan, John Core, Joe Weber, and workshop participants at the 2015 AAA Doctoral Consortium, the 2016 FARS Conference, MIT, the University of Rochester, and the University of Southern California. We gratefully acknowledge the financial support from the MIT Sloan School of Management.

3 1. Introduction In this paper, we examine inter-temporal variation in the externalities a firm s disclosures has on its peers (hereafter, disclosure externalities). 1 Recent research finds evidence that a firm s disclosure has important economic consequences for its peers. For example, a firm s disclosure (i) influences peer firms stock price, (ii) increases their stock liquidity, and (iii) facilitates their investment decisions (e.g., Foster, 1981; Bushee and Leuz, 2005; Badertscher et al., 2013). We extend this literature by examining the temporal changes in these disclosure externalities for firms that go from being newly public with limited information disclosed by the firm (henceforth, firmspecific information) to firms with longer histories of public disclosure that have relatively more firm-specific information available to investors. Our prediction is that peer-firm disclosures have larger economic effects on a firm s cost of capital when firm-specific disclosures are scarce, but that these externalities reduce over time as the amount of firm-specific information increases and substitutes for peer information. Our prediction relies on the idea that firms in an industry are affected by similar economic forces (e.g., common demand/supply shocks) and thus the disclosures of peer firms have spillover effects that reduce information asymmetry between managers and investors, as well as among investors, for all firms operating in that industry. Such reductions in information asymmetry can reduce financing costs (in both debt and equity markets), as illustrated in corporate finance models with adverse selection (Leland and Pyle, 1977; Myers and Majluf, 1984; Rock, 1986) or in asset pricing models with imperfect competition (Lambert et al., 2012). Insofar as peer-firm disclosures affect information asymmetry and financing costs, we predict that such disclosure externalities will vary over time as a function of the amount of firm- 1 By externalities, we mean the economic effects of disclosure that extend to firms beyond the disclosing firm. 1

4 specific information available to investors. Our intuition is similar to that presented in other streams of literature: for example, Lang (1991) develops an earnings response coefficient model in which uncertainly about firm value declines as investors observe a longer time-series of earnings realization (see also Pastor and Veronesi (2003) for similar argument in an asset pricing framework). Models in the executive compensation literature (e.g., Banker and Datar, 1989) show that the weights placed on different performance evaluation signals are proportional to its signalto-noise ratio. The intuition in our setting is that the disclosures provided by a firm are relatively less noisy than those provided by peer firms for valuing the disclosing firm s prospects, and thus we expect that peer-firm disclosures will become relatively less important as more information becomes available directly from the disclosing firm and substitutes for peer disclosures. 2 Nevertheless, ex ante there are several reasons why firm disclosures might not serve as substitutes for peer disclosures. For example, firm disclosures are often affected by managerial incentives to manipulate them, which can make them noisy and potentially less relevant than peer disclosures (we elaborate on these arguments in Section 2). We begin by testing our hypothesis using a sample of private firms that raise public debt for the first time. We focus on the public debt issuances of private firms for two main reasons: First, since private firms are not subject to SEC reporting requirements until they raise public capital, there is (i) relatively little firm-specific information available about them in the public domain prior to their public debt issuance and (ii) a significant increase in the amount of firmspecific information available about them in the years immediately following their public debt issuance. As a result, this setting is especially powerful for studying the decline in the importance 2 Prior research argues that firms are the lowest cost producers of corporate information (e.g., Coffee, 1984; Easterbrook and Fischel, 1984; Diamond, 1985) and thus a firm s disclosures about itself arguably has a lower signalto-noise ratio with respect to its own valuation than the disclosures provided by its peers. 2

5 of peer disclosure because the amount of firm-specific disclosure significantly increases in the years following the capital raising event. Second, by focusing on public debt, we can observe bond yields (a measure of the cost of the debt) at the time of issuance as well as over time in the years subsequent to the issuance. Proxies for the cost of debt (such as bond yields) are relatively less subject to measurement error concerns than proxies for the cost of equity capital, which are notoriously noisy (Elton, 1999; Easton and Monahan, 2005). Nevertheless, we recognize that there are some disadvantages to the public debt setting (e.g., a small sample of first-time bond issuers) and thus we also test our prediction in the context of firms raising equity capital. Drawing from the theoretical models on disclosure externalities (e.g., Dye, 1990; Admati and Pfleiderer, 2000), we construct our measure of peer-firm disclosures to capture: (i) the relevance of peer firms disclosures to non-disclosing firms, and (ii) the aggregate amount of information disclosed by peer firms. Specifically, we combine the degree of information transfer around earnings announcements within an industry to capture the relevance of a firm s disclosure to its peers (Foster, 1981; Pandit et al., 2011; Wang, 2014), and the percentage of public firms (relative to the total number of firms, public plus private) operating in the industry to capture the aggregate amount of industry information available from peer firms mandatory and voluntary disclosures (Badertscher et al., 2013). We find that peer-firm disclosure is negatively associated with bond yields at the time of issuance. 3 Specifically, a one standard deviation increase in our proxy for peer disclosure is associated with a 78 basis point decrease in bond yield (relative to a mean bond yield of 822 basis 3 As we discuss in more detail in Section 4.3.2, all of the bonds in our sample are initially issued to institutional investors as private placements under Rule 144A but are subsequently traded on public debt markets following SEC registration. In our main test, we measure bond yields at the time the bond is traded publicly (after its SEC registration) because this is when firms begin complying with the SEC s disclosure requirements and adverse selection concerns manifest. We then exploit the private placement window as an additional test (described below). 3

6 points for the sample, a relative decrease of 9.5%). This result is consistent with our initial prediction that peer disclosures affect other firms cost of capital when firm-specific information is scarce. We then turn to the inter-temporal changes in the effect of peer disclosure. We find that the effect of peer-firm disclosure on bond yields gradually declines from having a statistically significant effect in the first year of the bond issuance to a statistically insignificant effect in the third year post issuance. In economic terms, a one standard deviation increase in our proxy for peer disclosure lowers bond yields by 15% in the first year of its issuance, which declines to a 2% effect in third year post issuance. Similarly, when we break down our data into quarterly, rather than annual, observations, we observe a near monotonic decline in the relation between peer-firm disclosure and bond yields over the eight quarters following the bond issuance. These results are consistent with our prediction that peer-firm disclosure helps lower the cost of capital for other firms in the industry when firm-specific information is scarce and that this effect declines over time as the amount of firm-specific information increases. A potential concern with the above analyses is that our proxy for peer-firm disclosure could be correlated with industry-level changes in the cost of capital and/or other industry characteristics. For example, to the extent that firms are more likely to go public when the cost of capital is low, there could be an association between the percentage of public firms in an industry (an input into the construction of our measure) and the bond yields of firms in that industry. While such an argument does not explain the decay in the relation between peer disclosures and the cost of capital (as we document), it can explain the relation between peer disclosures and bond yields in the initial year of the bond issuance. We thus conduct a number of additional analyses to mitigate such endogeneity concerns. 4

7 We begin by conducting two additional tests in the bond market setting to corroborate our inference that the decay in the effect of peer-firm disclosure on the cost of capital is due to changes in the amount of firm-specific disclosure available to investors. First, we compare the effect of peer-firm disclosure for our sample of private firms to that of a matched sample of public firms. Since public firms have significantly richer information environments due to SEC disclosure requirements, voluntary disclosures, and information intermediary coverage, the importance of peer-firm disclosure to a public firm is likely to be lower than it is for an observably similar private firm. Consistent with this prediction, peer-firm disclosure has a significant effect on the yields of bonds issued by private firms, but an insignificant effect on the yields of bonds issued by public firms. This result is robust to matching the bonds of public and private firms by year, industry, and a number of firm characteristics, as well as different matching techniques, such as propensity score matching and entropy balanced matching (Hainmueller, 2012; McMullin and Schonberger, 2015). Second, we exploit an institutional feature of the bond market setting. Specifically, prior research finds that the vast majority of bonds are initially issued as Rule 144A private placements to institutional investors and are only subsequently registered with the SEC, which facilitates public trading of the bond (e.g., Fenn, 2000). Firms issuing bonds under Rule 144A are not required to comply with SEC disclosure requirements until they register the bond with the SEC. As a result, the amount of firm-specific information available to investors is largely unchanged from the time the firm initially issues a Rule 144A bond to the time it subsequently registers the same bond with the SEC. If the temporal change in the relation between peer-firm disclosure and bond yields is due to changes in the amount of firm-specific information available to investors (as we predict), we should not observe a decay in the relation between peer-firm disclosure and bond yields between the time the bond is issued under rule 144A and when it is subsequently registered with the SEC. Rather, the decay in this relation should occur only after the bond is registered with 5

8 the SEC. This is what we find. Specifically, the effect of peer-firm disclosure on bond yields increases (albeit insignificantly) from the time the bond is issued to the time it is SEC registered, and begins to fade only following SEC registration. Finally, we conduct three tests in an equity market setting to further validate our inferences. First, we test and find that peer-firm disclosures are negatively associated with bid-ask spreads (our proxy for the adverse selection component of the cost of capital) in the first year of a firm s initial public offering (IPO), but that this relation monotonically decreases over time in the three years subsequent to the IPO. Second, analogous to our test above, which compares private and public firms raising debt financing, we predict and find that peer-firm disclosures affect the bidask spreads of IPO firms and that this effect decays over time, but there is no such effect on the bid-ask spreads of a matched sample of seasoned equity offering (SEO) firms. Last, we test whether the effect of peer-firm disclosure increases as firm-specific information decreases. Specifically, we exploit changes in the amount of firm-specific disclosure caused by SEC rules that restricted firms from freely disclosing information prior to their equity offering (which is popularly known as gun-jumping provisions). 4 Shroff et al. (2013) find that bidask spreads increase during the SEO quiet period due to higher adverse selection arising from reduced firm-specific disclosures. We predict and find that peer-firm disclosures become relatively more important at that time, as shown by a significantly negative association between peer-firm disclosures and bid-ask spreads of SEO firms during their quiet period, when the SEC places 4 Section 5 (c) of the Securities Act of 1933 prohibits any firms from making any offer to sell a security prior to filing a registration statement with the SEC (the restriction period is known as the quiet period ). The definition of offer has grown to include any act that might contribute to conditioning the public mind or arousing public interest in the issuer (SEC release no. 3844), which is perceived as encompassing forward-looking voluntary disclosures such as management forecasts. Consistent with this perception, prior research documents a decrease in forward-looking disclosures prior to SEOs (e.g., Frankel et al., 1995; Lang and Lundholm, 2000; Shroff et al., 2013). Prior research also finds that voluntary disclosures such as management forecasts help lower a firm s bid-ask spreads, highlighting the economic importance of such firm-specific information (e.g., Coller and Yohn, 1997; Lang and Lundholm; 2000; Shroff et al., 2013; Balakrishnan et al., 2014). 6

9 restrictions on SEO firms disclosures. But we find no such effect in the periods adjacent to the quiet period. Importantly, the effect of peer-firm disclosure on bid-ask spreads during the quiet period disappears after the SEC relaxed quiet period disclosure restrictions by enacting the Securities Offering Reform in These results provide robust evidence that peer-firm disclosures affect bid-ask spreads when firm-specific disclosures are scarce, while mitigating endogeneity concerns that our results are driven by omitted variables. This paper contributes to the literature on the presence of externalities or peer effects of disclosure. A number of recent studies document that the disclosure of one firm affects the investment and stock prices of their peers (e.g., Sidak, 2003; Durnev and Mangen, 2008; Gleason et al., 2008; Badertscher et al., 2013; Chen et al., 2013; Shroff et al., 2014). We extend this literature by motivating and documenting the time-varying nature of such peer effects, which is in contrast to prior studies that document static effects. Our analyses also shed light on the mechanism through which peer effects change over time. We show that peer effects are particularly important for opaque firms with less firm-specific information available to investors. The importance of peer effects diminishes as more firm-specific information becomes available. Our evidence that externalities vary over time is also important in the context of disclosure regulation because such externalities are often one of the primary justifications for mandating disclosure. As Leuz and Wysocki (2015, Abstract) discuss, we generally lack evidence on marketwide effects and externalities from regulation, yet such evidence is central to the economic justification of regulation. Understanding the time-varying nature of externalities is important to assess the cumulative benefit of disclosure regulation via such peer-firm cost of capital effects. 2. Prior Research and Hypothesis 2.1. Related Literature 7

10 Our study builds on the literature examining the externalities (i.e., spillover effects) of disclosure. Beginning with Foster (1981), a large body of empirical research documents the presence of intra-industry information transfers. Information transfers refer to instances where one firm s disclosures affect the stock prices of other, related firms (typically in the same industry or along the supply chain). Prior studies document information transfers arising from news contained in earnings announcements (Foster, 1981), management forecasts (Baginski, 1987; Han et al., 1989), and transfers between buyers and suppliers in the same supply chain (Olsen and Dietrich, 1985; Pandit et al., 2011). These studies document a necessary condition for the presence of externalities, i.e., they provide evidence consistent with the assumption that firm values are correlated. However, information transfer studies only show that one firm s disclosure affects the stock price of other, related firms, without telling us whether the related firms would have independently disclosed the information if it had not been otherwise provided. 5 More recent studies try to directly tackle the question of whether disclosures generate positive or negative externalities. For example, Bushee and Leuz (2005) find that stricter disclosure regulation generates positive externalities in the form of increased stock liquidity. Badertscher et al. (2013) find that firms operating in industries with a larger proportion of public firms make better investment decisions (a result also consistent with disclosures having positive externalities). Durnev and Mangen (2008) find that misreporting by one firm can lead to distorted investment decisions by peer firms, suggesting that poor quality disclosure can generate negative externalities (also see Beatty et al., 2013; Chen et al., 2013; Shroff et al., 2014). 5 In other words, while Foster (1981) and others provide evidence that peer-firm disclosures have information transfers, they do not show whether these disclosures reduce information asymmetry. To the extent that the information transfers capture a substitution of news among firms, it is possible that peer-firm disclosures do not increase the aggregate information in the industry and information asymmetry might remain unchanged. 8

11 Despite the substantial literature documenting information transfers in stock prices and the more recent attempts to directly document disclosure externalities, Leuz and Wysocki (2015) note that the positive (or negative) externalities generated by such transfers remain relatively underresearched. 6 Our paper builds on prior research examining disclosure externalities by focusing on a single, specific angle that has been overlooked by prior research. Specifically, we focus on the changing nature of disclosure externalities and hypothesize that the importance of these externalities is a function of the relative amounts of firm-specific vs. peer-level disclosure available to investors. This focus on dynamic effects is in contrast to prior research, which assumes that the economic importance of externalities is constant over time. Understanding when and to what degree disclosure generates externalities is important because of its implications for regulation. One of the central justifications for disclosure regulation is that corporate disclosures tend to have externalities on other firms operating in the economy. The basic idea is that the disclosing firm typically would not internalize the benefit (or cost) of its disclosure to other firms in the economy when choosing its optimal disclosure policy. However, since the firms in an economy are typically affected by common economic factors, the disclosures of one can help inform others about common economy factors that affect the demand and supply of its products. In the presence of such positive spillover effects that disclosing firms might not consider when choosing their optimal level of disclosure, regulation that factors in the externalities of disclosure can be welfare enhancing for the economy as a whole. The analytical models presented in Dye (1990) and Admati and Pfleiderer (2000) formalize this idea and show that 6 The sentiment expressed by Leuz and Wysocki (2015) derives partly from the many prior studies examining disclosure externalities that do not successfully address the reflection problem as described by Manski (1993). The reflection problem is essentially the idea that the economic subjects belonging to a group (e.g., an industry) tend to behave similarly and thus could be responding to unobservable shocks to that group (e.g., industry growth opportunities). We attempt to mitigate this concern with a number of tests, discussed in Section 5. 9

12 disclosure regulation that encourages firms to disclose more precise information can increase social welfare under certain conditions Hypothesis Development Our hypothesis is based on three underlying arguments: (i) adverse selection concerns influence financing costs, (ii) peer-firm disclosures can reduce adverse selection costs for related firms, and (iii) disclosures provided by the firm about itself are more informative about its value than the disclosures of peer-firms. We discuss each of these arguments below in more detail to motivate our hypothesis but note that insofar as any of them are untrue, we might not find evidence supporting our hypothesis. The idea that adverse selection affects financing costs is well founded in the corporate finance literature. In the context of IPOs, Beatty and Ritter (1986) and Rock (1986) show that information asymmetry among investors creates uncertainty that is priced in equilibrium and increases financing costs. In a similar vein, Myers and Majluf (1984) show that adverse selection affect financing costs in secondary offerings as well as in debt offerings. Subsequent work shows that information asymmetry can also raise the cost of capital in an asset pricing model with multiple securities. For example, Lambert et al. (2012) show that in imperfectly competitive settings, information asymmetry between investors creates adverse selection costs, which increases expected returns. These theoretical arguments are supported by numerous empirical papers (see Beyer et al. (2010) and Leuz and Wysocki (2015) for reviews of the literature). The second argument underlying our hypothesis is that peer-firm disclosures reduce the adverse selection costs of related firms. The idea is that, to the extent that firms in an industry are affected by similar economic forces, greater disclosure by peer firms can have spillover effects for all firms operating in that industry. For example, Dye (1990) and Admati and Pfleiderer (2000) 10

13 develop analytical models that show positive externalities in the form of liquidity spillovers in capital markets. Specifically, they show that if firm values and cash flows are correlated, the disclosure of one firm is useful to investors in valuing other firms and increases the investors demand for shares in other firms. 7 Overall, prior analytical studies provide evidence that peer-firm disclosures help reduce information asymmetry in other firms, suggesting that they can have positive capital market effects. The final argument underlying our hypothesis is that the relative importance of peer-firm disclosure is a function of alternative sources of information that help reduce adverse selection costs. Even if peer-firm disclosure can reduce adverse selection costs, to the extent that investors have access to information directly disclosed by the firm, the spillover effects of peer-firm disclosure is likely to be small. Prior research argues that firms are the lowest cost producers of corporate information (Coffee, 1984; Diamond, 1985). Thus, disclosure provided directly by firms about themselves is potentially more precise and relevant for assessing their future prospects relative to the disclosures of peer firms. If so, the relative importance of peer-firm disclosures in reducing adverse selection costs depends on the amount of firm-specific disclosure available to investors. This argument is similar in spirit to the relative signal-to-noise ratio of the performance measures established in the compensation literature (Banker and Datar, 1989). Specifically, we argue that with respect to assessing a firm s future prospects, disclosures directly provided by a firm have a higher signal-to-noise ratio than do peer-firm disclosures. The intuition behind our prediction is also similar in spirit to that offered in Lang (1991) and Pastor and Veronesi (2003). For example, Lang (1991) develops and empirically tests a model in which uncertainty about firm 7 Lambert et al. (2007) make a similar point in the context of estimation risk. Specifically, they show that each firm s disclosure has an impact on investors assessed covariances for other firms, which in turn lowers other firms estimation risk and cost of capital. Lambert et al. (2007) argue that while these effects are likely to be small individually, they could be large across all firms in the market or economy. 11

14 value is greater for firms with a shorter time-series of earnings realizations. He finds that as investors observe a longer time-series of earnings (i.e., more firm-specific information in the parlance of our paper), uncertainty about future earnings is reduced. Pastor and Veronesi (2003) develop and test an asset pricing model in which investors attempting to value newly listed firms are confronted with greater uncertainty about their future profitability and such uncertainty resolves over time as investors learn more about them. Our hypothesis, motivated by the discussion above, is as follows: H: Peer-firm disclosures are negatively associated with cost of capital when firm-specific information is scarce and this negative association weakens as the amount of firm-specific information increases. Notwithstanding the above discussion, whether peer-firm disclosures affect the cost of capital and whether this association decays as the amount of firm-specific information increases is ultimately an empirical question. First, a large literature finds that firm disclosures can be affected by managerial incentives to increase stock prices and their compensation (see Dechow et al. (2010) for a review of the literature). Thus, even in the presence of a rich firm-specific disclosure environment, peer-firm disclosures could help reduce adverse selection costs since they are unlikely to be affected by the managerial incentives of related firms in the industry. In other words, given managerial incentives to obfuscate firm performance, it is plausible that peer-firm disclosures have a higher signal-to-noise ratio than the disclosures directly provided by a firm with respect to valuing its future prospects. Second, while we assume that firm-specific disclosures and peer-firm disclosures are substitutes, it is also conceivable that they are complements and help reinforce each other. As mosaic theory describes, many individual information items that might not be particularly relevant individually can, when joined together, be especially valuable to analysis. Specifically, Pozen (2005, p.639) states that the significance of one item of information may frequently depend upon 12

15 knowledge of many other items of information. Likewise, peer-firm disclosures can provide additional context for evaluating firm-specific disclosures, which can make these two sources of information complements rather than substitutes. The use of benchmarking in investment valuation exercises is an example consistent with the idea that firm and peer information might be complements. 3. Research Setting, Sample Selection and Research Design 3.1. Research Setting We use two settings to test our predictions. The first examines the public debt issuances of private firms before they begin complying with the SEC s ongoing disclosure requirements. There are two main reasons for this choice. First, this setting provides us with a sample of firms that are very opaque prior to their bond issuance but that become significantly more transparent following it. Specifically, private firms are not required to publicly disclose any information in the U.S. As a result, little is known about the operations and performance of private firms before they raise public finance. However, once a private firm decides to raise public capital (debt or equity), it is required to comply with the SEC s mandatory disclosure requirements, such as 10-K and 10-Q filings, which contain enormous amounts of information about firms and their operating environments. As a result, the amount of firm-specific information about a private firm significantly increases following a public debt issuance, thereby serving as a powerful setting for testing the changing role of peer-firm disclosure in mitigating information asymmetry and adverse selection costs. 8 Second, compared to the cost of capital measures available for equities, the debt 8 Further, in this setting: (i) the amount of peer-firm disclosure does not (necessarily) change over time, which mitigates endogeneity concerns that industry-wide disclosure practices are the result of changes in the industry-wide cost of capital or growth opportunities. And (ii) the change in the amount of firm-specific information is largely the result of changes in mandatory disclosure requirements that arise when a private firm issues public capital. Note that an analysis of externalities or the spillover effects of disclosure is less prone to endogeneity due to selection concerns (Leuz and Wysocki, 2015). That is, firms base their disclosure decisions on the private costs and benefits, not the 13

16 market setting allows us to employ a relatively clean and observable measure of the cost of capital: bond yields. Easton and Monahan (2005) evaluate a number of proxies for the cost of equity capital and conclude that most available proxies are unreliable and typically do not have a positive association with realized returns, even after controlling for the bias and noise in returns. Nevertheless, one potential drawback of the above setting is that there are relatively few instances of firms raising public debt (especially with no prior history of public disclosure). Thus, our second setting focuses on firms raising equity capital for the first time via initial public offerings (IPOs) and firms raising equity capital via seasoned equity offerings (SEOs) that are subject to significant disclosure restrictions due to the SEC s gun-jumping rules. The benefit of the IPO setting is that, similar to the public debt setting, these firms are relatively opaque prior to their capital raising event but their transparency significantly increases in the years following their IPO (Lang, 1991; Pastor and Veronesi, 2003). Further, IPOs occur far more frequently compared to public bond issuances (by firms not previously subject to the SEC s ongoing disclosure requirements). Finally, unlike the other settings in which there is an increase in firm-specific disclosure following the capital raising event, in our SEO setting, there is a reduction in the amount of firm-specific disclosure caused by a regulation (gun-jumping rules). Further, gun-jumping rules were relaxed in 2005, allowing us to better identify the relation between peer-firm disclosure and the cost of capital using a test akin to a difference-in-differences design Sample Selection Our bond sample consists of private firms that issue public debt between 1995 and We begin our sample selection in 1995 because the process we use to identify private firms that externalities of their decisions. Thus externalities are essentially an unintended outcome of a firm s disclosure, rather than a selected outcome. 14

17 have public bonds requires data from EDGAR; we end our sample in 2012 because our tests of changes in externalities over time uses three years of market data post-bond issuance and 2012 is the latest year with three years of subsequent market data. We follow the procedure outlined in Katz (2009) to identify private firms that have publicly traded debt. Specifically, we begin by selecting firm-year observations on Compustat that satisfy the following criteria: (i) the firm s stock price at fiscal year-end is missing, (ii) the firm has total debt as well as annual revenue exceeding $1 million, (iii) the firm is located in the U.S., and (iv) the firm is not a financial institution and does not operate in a regulated industry (SIC codes and ). This screening process yields an initial sample of 2,158 potentially private firms. However, many of these observations represent the pre-ipo fiscal years of IPO firms, which are required to include three years of historical information in their IPO prospectus. Removing the pre-ipo firm-years reduces the sample to 1,264 potential private firms. Next, we examine each of the remaining firms by hand and remove limited partnerships (LPs), the holding companies of public firms, and subsidiaries of public firms, reducing the sample to 914 potentially private firms. Next, we identify the subsample of these private firms that issue a bond between 1995 and We use Mergent s Fixed Income Securities Database (FISD) to identify bond issuances. We require the bond to be a non-convertible, fixed-rate issue categorized as a corporate debenture, and issued within the U.S. These requirements yield an initial sample of 10,822 bonds that we match to our sample of 914 potentially private firms. We match first on CUSIP, and then supplement the sample by hand-matching as many of the remaining unmatched firms to corporate bonds as possible. This matching and verification procedure yields a sample of 517 private firms that issued 1,044 public bonds between 1995 and

18 We find that Compustat is often missing key data items during the initial years following a firm s bond issuance, which is likely related to the fact that virtually all the bonds in our sample are initially issued as private placements under Rule 144A and are only subsequently issued to the public following their SEC registration (similar to that documented in Fenn (2000) and Livingston and Zhou (2002)). Private firms issuing bonds under Rule 144A are not required to comply with SEC disclosure requirements until they are registered with the SEC. Given the above circumstance, we supplement Compustat data by hand collecting key data items from Capital IQ for as many private firms as possible. This process yields a sample of 316 private firms that issue 578 public bonds for which we have the necessary data to conduct our analyses. We obtain daily bond yields from the Bloomberg terminal. Requiring Bloomberg data leaves us with a sample of 165 private firms and 278 bonds with traded yield data. Since our primary interest is in firms raising capital for the first time (when firm-specific information is scarce), we retain only those bonds issued within the first filing period of the firm. That is, we retain the all bonds issued by a firm before its first annual filing with the SEC. This further reduces the sample to 165 private firms and 209 bonds. Finally, our tests of the temporal changes in the association between peer-firm disclosure and bond yields require three consecutive years of traded bond yields following the bond issuance. This requirement reduces our final sample to 65 private firms that issue 73 traded bonds. Table 1, Panel A outlines our sample selection procedure in detail and Table 2 shows the distribution of bonds by year. Panels B and C explain the sample selection for our tests using IPOs and SEOs. We collect a sample of IPOs from 1995 to 2005 and SEOs from 2003 to 2008 from the Thomson Financial Securities Data Corporation (SDC) new issues database. Our IPO sample ends in 2005 because we use the marginal effective spread computed using TAQ data (following Akins et al. (2012)), and 16

19 we could obtain this measure only until Further, since we require three years of spread data following the IPO, we end our IPO sample in For our SEO sample selection, we follow Shroff et al. (2013) and focus on the three year periods centered on the 2005 Securities Offering Reform. We follow the procedure in Loughran and Ritter (2004) to create our sample of IPOs and the procedure in Shroff et al. (2013) for our sample of SEOs. Applying the procedure in Loughran and Ritter (2004) yields an initial sample of 1,640 IPOs from 1995 to Data requirements for the control variables and the three consecutive years of bid-ask spreads reduce our sample size to 843 IPOs. Requiring a propensity score matched SEO issued in the same year and industry further reduces our sample to 365 IPOs that have matching SEOs. For our quiet period analyses, we restrict our sample to those SEOs completed three years before and after the 2005 Securities Offering Reform (following Shroff et al. (2013)), which yields a sample of 382 (275) SEOs from 2003 to 2005 (2006 to 2008) Research Design We estimate the following regressions to test our main predictions: Bond Yieldi,t = αt + αind + β1 Peer Disclosurei,t-1 + ɤ X + ϵi,t. (1) Bond Yieldi,t = αt + αind + β1 Peer Disclosurei,t-1 Year 1i,t + β2 Peer Disclosurei,t-1 Year 2i,t + β3 Peer Disclosurei,t-1 Year 3i,t + β4 Year 1i,t + β5 Year 2i,t + β6 Year 3i,t + ɤ X + ϵi,t. (2) In the equations above, i, t, and ind indexes firms, years, and industries; respectively, and are year and industry fixed effects. 9 The dependent variable, Bond Yield, is computed as the excess of a bond s yield-to-maturity over that of a matched Treasury bond that has a similar remaining time-to-maturity and the closest coupon rate to that of the sample bond (Bharath et al., 2008; Guedhami and Pittman, 2008; Badertscher et al., 2015). We use the average traded yield in year 9 Due to limited sample size, we use the Fama-French 12-digit industry classifications for our fixed effects. In untabulated analyses, we perform all of our tests with 2-digit NAICS fixed effects and find similar results. 17

20 t to compute Bond Yieldt. Peer Disclosure is our proxy for peer-firm disclosure and X is a vector of control variables based on prior research and described in detail in the appendix (e.g., Bharath et al., 2008; Guedhami and Pittman, 2008; Saunders and Steffen, 2011). Year 1 (Year 2, Year 3) is an indicator variable that equals one for first (second, third) year following the bond issuance. 10 Note that these indicator variables are unique to the bond and thus are not subsumed by year fixed effects. The intuition behind including them in our regressions is to capture systematic changes in bond yields in the years following its issuance (e.g., to capture any market timing associated with bond issuances). We cluster standard errors at the 4-digit NAICS industry level. All continuous variables are winsorized at the 1% and 99% levels each year. Equation 1 is used to test the effect of peer-firm disclosure on bond yields and equation 2 is used to test the change in this relation over time. The variable of interest in equation 1 is Peer Disclosure and our prediction is that the coefficient on this variable will be negative, implying that an increase in Peer Disclosure is associated with a decrease in the cost of capital. The variables of interest in equation 2 are Peer Disclosure Year 1, Peer Disclosure Year 2, and Peer Disclosure Year 3, and our prediction is that the coefficients on first variable will be larger than that on the second, which will be larger than that on the third (i.e., β1 > β2 > β3 ), implying that the relation between Peer Disclosure and the cost of capital decays over time Measuring Peer-Firm Disclosure Drawing from the theoretical models on disclosure externalities (e.g., Dye, 1990; Admati and Pfleiderer, 2000), we construct our measure of peer-firm disclosure to capture: (i) the relevance of peer firms disclosures to non-disclosing firms, and (ii) the amount of information disclosed by 10 Equation 2 is estimated such that we cannot include a main effect for Peer Disclosure. Rather, the coefficient on Peer Disclosure Year 1 should be interpreted as the total (not incremental) effect of Peer Disclosure on Bond Yield in Year 1. Peer Disclosure Year 2 and Peer Disclosure Year 2 should be interpreted as total effects. 18

21 peer firms in aggregate. Specifically, we measure peer-firm disclosure (Peer Disclosure) by multiplying (i) the information transfers within an industry (Info. Transfer) and (ii) the percentage of public firms operating in the industry (%Public). We measure Info. Transfer following Wang (2014). Specifically, we designate the five largest firms in each Fama-French 48 industry as market leaders and estimate the market reaction of all non-announcing firms in the industry to the unexpected earnings of the market leaders. This procedure provides us with an estimate of the sensitivity of the peer firms stock price to the unexpected earnings of the market leaders in the industry; we estimate these regressions at the industry-year level and the coefficient on unexpected earnings serves as our proxy for the amount of information transfer in an industry-year (see the appendix for a detailed description of the proxy). The intuition behind this proxy is that a firm s market reaction to the earnings surprise of another firm is likely to increase with the strength of their economic ties. That is, when a firm announcing earnings is affected by the same economic forces that affect the value of another firm (that is not simultaneously announcing earnings), the announcing firm s earnings news is likely to be informative in valuing the non-announcing firm, and the relevance of such earning information is greater for firms with closer economic links. Thus, industries in which firms are closely linked and affected by common economic factors are also likely to have larger stock price reactions to the earnings surprise of their industry peers. We measure %Public following Badertscher et al. (2013). We obtain data on the total number of firms within each 4-digit NAICS industry from the Census Bureau, and proxy for the number of public firms in each industry using Compustat. 11 %Public is the number of public firms 11 Note that during our sample period, the Census Bureau data are only available for 1992, 1997, 2002, 2007, and Thus, to obtain the total number of firms for the intervening years, we follow Badertscher et al. (2013) and interpolate using the values available at five-year intervals. 19

22 scaled by the total number of firms within an industry. The intuition behind this measure is that the composition of private and public firms in an industry affects the industry s information environment because public firms are subject to numerous mandatory disclosure requirements (and also have voluntary disclosure incentives) but that private firms are not subject to such disclosure requirements (and do not share the same disclosure incentives). As a result, industries composed of a greater percentage of public firms have a richer and more transparent information environment than industries composed of a smaller percentage of public firms. 12 We convert both Info. Transfer and %Public into a ranked variable by sorting industries into quintiles every year, with quintile five (one) representing industries with the greatest (smallest) information transfer and public firm presence. We then multiply Info. Transfer and %Public (both in quintile ranks) to compute our proxy for peer-firm disclosure. We scale Peer Disclosure to be bounded between zero and one for ease of interpretation. 4. Results 4.1. Descriptive Statistics Table 3 presents the descriptive statistics for the variables used in our analyses. Panel A presents the descriptives for the larger sample of 209 bonds for which we do not require three years of traded yields and Panel B presents the descriptives for the smaller sample of 73 bonds with three years of yield data. In Panel A (B), the average firm has total assets worth $2,140 ($1,967) million, a leverage ratio (long-term debt scaled by total assets) of 0.70 (0.66), and a tangible asset ratio of 0.43 (0.42). Further, the average firm in our sample is fairly profitable with an EBITDA to sales 12 An alternative proxy for the amount of public disclosure in an industry is the number of public firms in the industry (rather than the percentage). However, a limitation of using the number of public firms in the industry is that it is closely related to industry size and does not necessarily provide an estimate of how comprehensive the public disclosure environment is in the industry. 20

23 ratio of 0.17 (0.16) in Panel A (B), and a growth rate of 17% (11%) in sales in Panel A (B). 13 Finally, the average Bond Yield in our sample is 822 basis points over a matched sample of Treasury yields, the average bond has a maturity of 100 months, and the average loan amount is $307 million. These characteristics are largely consistent with those found in prior research examining private firms with public debt, such as Katz (2009), Givoly et al. (2010), and Badertscher et al. (2014). Panel C presents the correlation matrix. The Pearson (Spearman) correlation between Bond Yield and Peer Disclosure is (-0.12), indicating that peer-firm disclosure is negatively associated with the cost of debt capital, consistent with our hypothesis Temporal Changes in the Relation between Peer-Firm Disclosure and Bond Yields Table 4 presents the results from a regression of bond yields on peer-firm disclosure and control variables (equation 1). The first column shows that the coefficient on Peer Disclosure is negative and statistically significant (coef.=-2.80; t-stat.=-3.51). This coefficient indicates that firms raising public debt (prior to their first SEC filing period) have lower yield spreads if they operate in industries with greater peer-firm disclosure, consistent with our argument that peer-firm disclosure helps lower adverse selection costs. In economic terms, a one standard deviation increase in Peer Disclosure is associated with a 78 basis point decrease in Bond Yield. The average Bond Yield in our sample is 822 basis points, implying that Peer Disclosure is associated with a 9.5% decrease in Bond Yield in the first year of the bond issuance. Table 4 also shows that the control variables are largely consistent with our expectations and prior research. For example, larger and more profitable firms have lower yields. 13 Katz (2009) and Badertscher et al. (2014) report descriptives for ROA, not EBITDA over sales. The average ROA for our sample firms is 0.00 (untabulated), which is similar to the ROA reported their papers. 21

24 In the next two columns in Table 4, we examine whether the relation between Peer Disclosure and Bond Yield is robust to controlling for the amount of firm-specific information disclosed at the time of the bond issuance. We proxy for firm-specific disclosure (Firm Disclosure) using the proxy introduced by Chen et al. (2015), which captures the level of disaggregation in a firm s financial statements. Empirically, Chen et al. (2015) construct their measure by counting the number of unique line items in a firm s balance sheet and income statement. Requiring this variable for our analyses reduces the sample size from 209 to 172 bonds. To better understand the effect of controlling for Firm Disclosure, we re-estimate our primary regression (before controlling for Firm Disclosure) using the smaller sample of 172 observations, and then present the results for the same sample controlling for Firm Disclosure in the third column. As expected, Firm Disclosure is negatively associated with bond yields, but we find that the coefficient on Peer Disclosure continues to be negative and statistically significant (coef.=-2.52; t-stat.=-3.29). Further, the coefficient estimate for Peer Disclosure is very similar in the regression that does not control for Firm Disclosure (coef.=-2.62; t-stat.=-3.51), suggesting that excluding Firm Disclosure from our subsequent tests is unlikely to create a correlated omitted variable bias. Overall, these results are consistent with our prediction that peer-firm disclosures affect a firm s cost of capital and that this effect is incremental to that of firm-specific disclosures at the time of bond issuance. Next, we examine our main hypothesis on the dynamic effect of peer-firm disclosure on the cost of capital. We perform our dynamic tests on a subsample of our private firm bonds that have three consecutive years of traded yield data following the bond issuance. By restricting our sample to bonds with three consecutive years of yield data, we ensure that changes in the sample composition over time do not affect our inference. We estimate equation 2 to test our hypothesis. The results of this estimation are reported in Table 5. 22